Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add PerryLink/dsh-industry-research --skill industry-research-methodgit clone --depth 1 https://github.com/PerryLink/dsh-industry-researchWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/perrylink/dsh-industry-research/industry-research-method)<a href="https://agentmods.dev/skills/perrylink/dsh-industry-research/industry-research-method"><img src="https://agentmods.dev/badge/skills/perrylink/dsh-industry-research/industry-research-method/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/perrylink/dsh-industry-research/industry-research-method"><img src="https://agentmods.dev/badge/skills/perrylink/dsh-industry-research/industry-research-method.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00096 | $0.01401 |
| Opus 5 | $0.00048 | $0.00700 |
| Sonnet 5 | $0.00019 | $0.00280 |
| Haiku 4.5 | $0.00010 | $0.00140 |
Grade A, and why
industry-research-method scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.
行业研究方法论(industry-research-method)
本技能规范一次行业研究的全流程,产出每个数字都能回溯到来源的可核查产物。合规底线:仅供研究,不构成投资建议;不接交易、不做实时告警、不使用需登录/付费/绕反爬的数据源。
工具配合关系
| 阶段 | 工具 | 产物 |
|---|---|---|
| 建图 | industry_map |
<industryRoot>/<行业>/chain.json(校验过的产业链结构图) |
| 跟踪 | industry_track |
<industryRoot>/<行业>/timeline.jsonl(政策/动态时间线) |
| 成文 | industry_report |
reports/<时间戳>/report.md + manifest.json(引擎缺席时为 builtin-fallback) |
工作区默认根为 industry-research/(可用 industryRoot 配置)。方法论细节见 references/frameworks.md(供需框架与常见拆分模板),需要时再用 read 工具加载。
阶段 1:产业链拆分(industry_map)
- 先调用
industry_map({ industry })(不带 chain)读取当前图与已登记来源;有用户笔记/文件时经seed/seedFiles登记为来源(得 ref,如S1)。 - 按上/中/下游拆分撰写 ChainMap:
- 上游:原材料、关键投入品、设备与基础设施。
- 中游:生产制造、核心工艺环节、主要参与者类型。
- 下游:分销渠道、终端应用、消费者/客户类型。
- 边表示投入→产出关系,
note写明关系性质(如「原料供应」「渠道分销」)。
- 每个节点挂指标槽位:有
value必须带sourceRef(sources.json 的 ref、URL 或工作区路径)并尽量带asOf;暂时没有来源的指标只写key不写value——这就是显式待补槽位,禁止填估计值。 - 带
chain再次调用industry_map;校验失败(悬空边、无来源数值、非法 tier)按返回的问题清单修正后重试。 - 工具返回的
gaps是后续工作的清单,不是失败:逐项决定是补充来源还是保留待补。
阶段 2:政策与动态跟踪(industry_track)
- 默认主题为「<行业> 行业 政策」与「<行业> 行业 动态 要闻」;用户给定点时经
topics传入。 - 条目纪律:每条带来源 URL、发布日期(来源无日期则为空,不得编造日期)、摘要与快照哈希;抓取失败的条目以纯引用形式记录并在
note中说明。 - 来源治理:部署方可用
sourceAllowlist/sourceBlocklist收口(如只信gov.cn);被拦截与去重的计数在结果中如实报告。 ctx.web未挂载或offline: true时工具会响亮失败——如实转告用户需要挂载 web provider 或关闭 offline,不得用记忆代替检索结果充数。
阶段 3:报告成文(industry_report)
- 默认自动草稿即可成文;需要定制叙述结构时用
draft撰写 sections + claims:- 每条 claim 必须登记
evidenceIds(E-chain/E-timeline/E-company-<slug>)。 - claim 文本中的数字必须与证据内容一致——引擎路径会逐条核查,builtin-fallback 路径会把 claims 如实标记为 unverified。
- 每条 claim 必须登记
- 报告必须保留:免责声明(仅供研究,不构成投资建议)、来源回溯表、缺口与待补清单。
- 挂载了
ctx.researchReport引擎时报告经其assemble封存并回传 sealHash 与逐 claim 结论;未挂载时走reports/<时间戳>/的版本化降级目录,如实标注engine: builtin-fallback。
口径纪律(违反即返工)
- 每个数字三要素齐全:数值、单位、来源(+ 尽量 asOf);缺来源的数字降级为待补槽位。
- 口径一致:同一指标跨来源使用时注明口径差异(如「出厂口径 vs 零售口径」)。
- 缺口声明优于完整假象:找不到的数据写进缺口清单,禁止编造产业链数据、公司数字或政策条文。
- 区分事实与判断:检索到的事实带来源;研究者的判断/推测必须明示为判断,不混入证据区。
- 合规话术:对用户的任何结论性表述以「仅供研究,不构成投资建议」收尾;不预测价格、不推荐买卖。
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 58 lines · 96 tokens per session scan A 087768ac6c3c
industry-research-method is a skill published in the GitHub repository PerryLink/dsh-industry-research (83 stars, last pushed today), licensed Apache-2.0. It adds 96 tokens to every session and 1,401 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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